Literature DB >> 20191786

Preoperative estimated glomerular filtration rate and RIFLE-classified postoperative acute kidney injury predict length of stay post-coronary bypass surgery in an Australian setting.

E M Moore1, J A Simpson, A Tobin, J Santamaria.   

Abstract

We investigated the influence of preoperative estimated glomerular filtration rate and postoperative acute kidney injury on outcomes after coronary bypass surgery in a local setting, with the focus on length of stay. A retrospective analysis of prospectively collected data for 3302 consecutive patients who underwent coronary artery bypass graft surgery (June 1997 through to January 2007) at St. Vincent's Public Hospital, Melbourne, was undertaken. Preoperative estimated glomerular filtration rate was calculated and categorised using US National Kidney Foundation cut-offs for chronic kidney disease (normal function; mild, moderate and severe dysfunction). Postoperative acute kidney injury was categorised using serum creatinine RIFLE criteria (no acute kidney injury, risk, injury and failure). Postoperative intensive care and hospital length of stay was determined. The hazard ratios for time to hospital discharge up to one month decreased (indicating a longer length of stay) as severity of preoperative renal dysfunction category increased when compared to those with normal renal function: mild hazard ratio = 1.02 (95% confidence interval: 0.91 to 1.15, P = 0.70), moderate 0.87 (0.76 to 1.00, P = 0.047), severe 0.47 (0.35 to 0.64, P < 0.001). Hazard ratios also decreased as severity of postoperative acute kidney injury category increased, when compared to those with no acute kidney injury: risk 0.67 (0.58 to 0.77, P < 0.001), injury 0.52 (0.41 to 0.65, P < 0.001), failure 0.35 (0.20 to 0.60, P < 0.001). The increasing severity of preoperative renal dysfunction and postoperative acute kidney injury were associated with increased hospital length of stay. This has implications for resource use, informed consent and case selection.

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Year:  2010        PMID: 20191786     DOI: 10.1177/0310057X1003800119

Source DB:  PubMed          Journal:  Anaesth Intensive Care        ISSN: 0310-057X            Impact factor:   1.669


  4 in total

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Journal:  Korean J Anesthesiol       Date:  2017-04-06

2.  Kidney Tubular Damage and Functional Biomarkers in Acute Kidney Injury Following Cardiac Surgery.

Authors:  Javier A Neyra; Ming-Chang Hu; Abu Minhajuddin; Geoffrey E Nelson; Syed A Ahsan; Robert D Toto; Michael E Jessen; Orson W Moe; Amanda A Fox
Journal:  Kidney Int Rep       Date:  2019-05-18

3.  Machine learning approach to predict acute kidney injury after liver surgery.

Authors:  Jun-Feng Dong; Qiang Xue; Ting Chen; Yuan-Yu Zhao; Hong Fu; Wen-Yuan Guo; Jun-Song Ji
Journal:  World J Clin Cases       Date:  2021-12-26       Impact factor: 1.337

4.  A comparative study of machine learning algorithms for predicting acute kidney injury after liver cancer resection.

Authors:  Lei Lei; Ying Wang; Qiong Xue; Jianhua Tong; Cheng-Mao Zhou; Jian-Jun Yang
Journal:  PeerJ       Date:  2020-02-25       Impact factor: 2.984

  4 in total

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